Principal AI/ML Architect, Applied Field Engineering
Snowflake- Full Time
- Senior (5 to 8 years)
Candidates should possess 5-7 years of experience in ML System Architecture & Design, with demonstrated proficiency in Databricks, Snowflake, and SageMaker. They should also have experience with Performance Optimization and Model Monitoring setup.
The ML Architect will collaborate with Data Scientists and the AI/ML community to translate business problems into scalable ML solutions, define model serving strategies, design and implement an ML Experimentation Platform, standardize ML pipelines, and manage model governance and compliance. They will develop and maintain a feature repository, build and own the ML Portfolio based on business unit needs, and support ML infrastructure as an administrator on Databricks, Snowflake, and Sagemaker, while also owning and publishing best practices.
Develops AI tools for sustainable agriculture
Mineral.ai develops technology solutions aimed at improving the agriculture industry. The company utilizes perception technology, artificial intelligence (AI), and machine learning (ML) to create tools that help farmers, researchers, and agricultural advisors increase crop yields, manage pests, and adapt to climate change. Their products include precision agriculture tools that optimize resource use and advanced data analytics platforms that provide insights from agricultural data. Unlike many competitors, Mineral.ai focuses on creating partnerships within the agriculture sector to co-develop solutions, enhancing their product offerings. The goal of Mineral.ai is to support sustainable food production and help feed the world more efficiently.